Nowadays, robots are applicable in various areas of our life. To name some examples: A massive industrial robot, which works in a production line to deal with car body panels, a gantry robot, which sorts different objects, a military robot, which cleans a mine field for instance and last but not least the neighbours-robotic lawn mower. Robotics deal with topics of varied disciplines. This diploma thesis is dedicated to a subtopic of robotics, namely the assistance of old people in their everyday life by an auxiliary mobile robot named Hobbit. In this context the goal of this thesis is to find a way of evaluating the detection of successful grasping. This has to be accomplished only on the base of visual information, which is provided by the Microsoft Kinect camera. In the course of the thesis, different approaches of solving this problem will be presented, whereby the edge detection approach, the SIFT approach of comparing regional features and the approach of detection with AR-Markers were implemented. All these solutions were experimentally evaluated. Applying the Hobbit-planar grippers, the option of using AR-markers for grasp detection emerged as especially effective, as it is robust, fast, easy to implement and reliable, even if small objects are being investigated. The implementation, which took place through a ROS-package, has proven itself in practice and can be used and ported for all planar grippers